GHA_1998_GLSS_v01_M_v01_A_SHIP
Living Standards Survey IV 1998-1999 - World Bank SHIP Harmonized Dataset
Name | Country code |
---|---|
Ghana | GHA |
Living Standards Measurement Study [hh/lsms]
Sample survey data [ssd]
The SHIP datasets contains harmonized variables, produced by Africa Region, Office of the Chief Economist (AFRCE) based on the raw data from houshold surveys conducted in African countries.
2012-06-18
The data provided by the National Statistical Office is harmonized across countries and across time using a standard SHIP methodology.
The scope of the SHIP files includes:
National
The survey covered all de jure household members (usual residents).
Name |
---|
Ghana Statistical Service (GSS) |
Name | Affiliation | Role |
---|---|---|
Office of the Chief Economist - Africa Region | World Bank | Data Harmonization |
SAMPLE DESIGN FOR ROUND 4 OF THE GLSS
A nationally representative sample of households was selected in order to achieve the survey objectives.
Sample Frame
For the purposes of this survey the list of the 1984 population census Enumeration Areas (EAs) with population and household information was used as the sampling frame. The primary sampling units were the 1984 EAs with the secondary units being the households in the EAs. This frame, though quite old, was considered inadequate, it being the best available at the time. Indeed, this frame was used for the earlier rounds of the GLSS.
Stratification
In order to increase precision and reliability of the estimates, the technique of stratification was employed in the sample design, using geographical factors, ecological zones and location of residence as the main controls. Specifically, the EAs were first stratified according to the three ecological zones namely; Coastal, Forest and Savannah, and then within each zone further stratification was done based on the size of the locality into rural or urban.
SAMPLE SELECTION
EAs
A two-stage sample was selected for the survey. At the first stage, 300 EAs were selected using systematic sampling with probability proportional to size method (PPS) where the size measure is the 1984 number of households in the EA. This was achieved by ordering the list of EAs with their sizes according to the strata. The size column was then cumulated, and with a random start and a fixed interval the sample EAs were selected.
It was observed that some of the selected EAs had grown in size over time and therefore needed segmentation. In this connection, such EAs were divided into approximately equal parts, each segment constituting about 200 households. Only one segment was then randomly selected for listing of the households.
Households
At the second stage, a fixed number of 20 households was systematically selected from each selected EA to give a total of 6,000 households. Additional 5 households were selected as reserve to replace missing households. Equal number of households was selected from each EA in order to reflect the labour force focus of the survey.
NOTE: The above sample selection procedure deviated slightly from that used for the earlier rounds of the GLSS, as such the sample is not self-weighting. This is because,
Start | End |
---|---|
1998-04 | 1999-03 |
Name | Affiliation | |
---|---|---|
Office of the Chief Economist, Africa Region | World Bank | Xye@worldbank.org |
Use of the dataset must be acknowledged using a citation which would include:
The user of the data acknowledges that the original collector of the data, the producer of the SHIP Harmonized Dataset, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Name | Affiliation | |
---|---|---|
Office of the Chief Economist, Africa Region | World Bank | Xye@worldbank.org |
Office of the Chief Economist, Africa Region | World Bank | Sshome@worldbank.org |
DDI_GHA_1998_GLSS_v01_M_v01_A_SHIP
Name | Affiliation | Role |
---|---|---|
Office of the Chief Economist, Africa Region | World Bank | Produce and document SHIP data |
2012-06-18
Version 01 (June 2012)
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